Optimization Methods for Travelling Salesman Problem

Three exact algorithms (Brute Force Search (BFS), Dynamic Programming (Held-Karp: HK), and Branch and Bound (B&B)), two heuristic algorithms

three exact algorithms (Brute Force Search (BFS), Dynamic Programming (Held-Karp: HK), [IA1] and Branch and Bound (B&B)[IA2] ), two heuristic algorithms (Nearest Neighbor (NN)[IA3] and Christofides' Algorithm (CA)[IA4] ), and three meta-heuristic techniques (Artificial Bee Colony (ABC)[IA5] , Genetic Algorithm (GA), and Tree-Seed Algorithm (TSA)[IA6] )

[IA1]Poremba, Michael. Dynamic Programming-Based Algorithms and Heuristics for Routing Problems. Diss. University of Southern California, 2017.

[IA2]Morrison, David R., et al. "Branch-and-bound algorithms: A survey of recent advances in searching, branching, and pruning." Discrete Optimization 19 (2016): 79-102.

[IA3]AlSalibi, Besan A., Marzieh Babaeian Jelodar, and Ibrahim Venkat. "A comparative study between the nearest neighbor and genetic algorithms: A revisit to the traveling salesman problem." International Journal of Computer Science and Electronics Engineering (IJCSEE) 1.1 (2013): 110-123.

[IA4]Balas, Egon, and Nicos Christofides. "A restricted Lagrangean approach to the traveling salesman problem." Mathematical Programming 21.1 (1981): 19-46.

[IA5]Karaboga, Dervis, and Beyza Gorkemli. "Solving traveling salesman problem by using combinatorial artificial bee colony algorithms." International Journal on Artificial Intelligence Tools 28.01 (2019): 1950004.

[IA6]Demir, Emre, and İbrahim Aydoğdu. "Transportation path assignment within the airports in Turkey." International Conference on Harmony Search Algorithm. Singapore: Springer Singapore, 2020.